Latent Semantic Analysis

The basic idea of latent semantic analysis (LSA) is, that text do have a higher order (=latent semantic) structure which, however, is obscured by word usage (e.g. through the use of synonyms or polysemy). By using conceptual indices that are derived statistically via a truncated singular value decomposition (a two-mode factor analysis) over a given document-term matrix, this variability problem can be overcome.


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Reference manual

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install.packages("lsa")

0.73.1 by Fridolin Wild, 5 years ago


Browse source code at https://github.com/cran/lsa


Authors: Fridolin Wild


Documentation:   PDF Manual  


Task views: Natural Language Processing


GPL (>= 2) license


Depends on SnowballC

Suggests tm


Imported by CoreGx, DCD, DTWBI, DTWUMI, DiffNet, FSMUMI, IBCF.MTME, IntClust, SemNeT.

Depended on by AurieLSHGaussian, LSAfun, RWBP.

Suggested by quanteda.


See at CRAN